Microarchitectural analysis of a GPU implementation of the most apparent distortion image quality assessment algorithm

Vignesh Kannan, Joshua Holloway, Sohum Sohoni, Damon M. Chandler

    Research output: Contribution to journalConference article

    2 Citations (Scopus)

    Abstract

    Due to the massive popularity of digital images and videos over the past several decades, the need for automated quality assessment (QA) is greater than ever. Accordingly, the impetus on QA research has focused on improving prediction accuracy. However, for many application areas, such as consumer electronics, the runtime performance and related computational considerations are equally as important as the accuracy. Most modern QA algorithms exhibit a large computational complexity. However, the large complexity of these algorithms does not necessarily prohibit their ability of achieving low runtimes if hardware resources are used appropriately. GPUs, which offer a large amount of parallelism and a specialized memory hierarchy, should be well-suited for QA algorithm deployment.

    Original languageEnglish (US)
    Pages (from-to)36-41
    Number of pages6
    JournalIS and T International Symposium on Electronic Imaging Science and Technology
    VolumePart F130046
    DOIs
    StatePublished - Jan 1 2017

    Fingerprint

    Image quality
    Consumer electronics
    Computational complexity
    hierarchies
    Hardware
    Data storage equipment
    resources
    hardware
    Graphics processing unit
    predictions
    electronics

    ASJC Scopus subject areas

    • Computer Graphics and Computer-Aided Design
    • Computer Science Applications
    • Human-Computer Interaction
    • Software
    • Electrical and Electronic Engineering
    • Atomic and Molecular Physics, and Optics

    Cite this

    Microarchitectural analysis of a GPU implementation of the most apparent distortion image quality assessment algorithm. / Kannan, Vignesh; Holloway, Joshua; Sohoni, Sohum; Chandler, Damon M.

    In: IS and T International Symposium on Electronic Imaging Science and Technology, Vol. Part F130046, 01.01.2017, p. 36-41.

    Research output: Contribution to journalConference article

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